[HTML][HTML] Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: A review
Diffusion magnetic resonance imaging (dMRI) tractography is an advanced imaging
technique that enables in vivo reconstruction of the brain's white matter connections at …
technique that enables in vivo reconstruction of the brain's white matter connections at …
A review of predictive and contrastive self-supervised learning for medical images
WC Wang, E Ahn, D Feng, J Kim - Machine Intelligence Research, 2023 - Springer
Over the last decade, supervised deep learning on manually annotated big data has been
progressing significantly on computer vision tasks. But, the application of deep learning in …
progressing significantly on computer vision tasks. But, the application of deep learning in …
Volumetric white matter tract segmentation with nested self-supervised learning using sequential pretext tasks
Q Lu, Y Li, C Ye - Medical Image Analysis, 2021 - Elsevier
White matter (WM) tract segmentation based on diffusion magnetic resonance imaging
(dMRI) provides an important tool for the analysis of brain development, function, and …
(dMRI) provides an important tool for the analysis of brain development, function, and …
[HTML][HTML] Deep fiber clustering: anatomically informed fiber clustering with self-supervised deep learning for fast and effective tractography parcellation
White matter fiber clustering is an important strategy for white matter parcellation, which
enables quantitative analysis of brain connections in health and disease. In combination …
enables quantitative analysis of brain connections in health and disease. In combination …
A survey of the impact of self-supervised pretraining for diagnostic tasks in medical X-ray, CT, MRI, and ultrasound
Self-supervised pretraining has been observed to be effective at improving feature
representations for transfer learning, leveraging large amounts of unlabelled data. This …
representations for transfer learning, leveraging large amounts of unlabelled data. This …
A systematic review of automated methods to perform white matter tract segmentation
White matter tract segmentation is a pivotal research area that leverages diffusion-weighted
magnetic resonance imaging (dMRI) for the identification and mapping of individual white …
magnetic resonance imaging (dMRI) for the identification and mapping of individual white …
Deep diffusion MRI registration (DDMReg): a deep learning method for diffusion MRI registration
F Zhang, WM Wells, LJ O'Donnell - IEEE transactions on …, 2021 - ieeexplore.ieee.org
In this paper, we present a deep learning method, DDMReg, for accurate registration
between diffusion MRI (dMRI) datasets. In dMRI registration, the goal is to spatially align …
between diffusion MRI (dMRI) datasets. In dMRI registration, the goal is to spatially align …
A survey of the impact of self-supervised pretraining for diagnostic tasks with radiological images
Self-supervised pretraining has been observed to be effective at improving feature
representations for transfer learning, leveraging large amounts of unlabelled data. This …
representations for transfer learning, leveraging large amounts of unlabelled data. This …
Knowledge transfer for few-shot segmentation of novel white matter tracts
Q Lu, C Ye - Information Processing in Medical Imaging: 27th …, 2021 - Springer
Convolutional neural networks (CNNs) have achieved state-of-the-art performance for white
matter (WM) tract segmentation based on diffusion magnetic resonance imaging (dMRI) …
matter (WM) tract segmentation based on diffusion magnetic resonance imaging (dMRI) …
DFC: anatomically informed Fiber clustering with self-supervised deep learning for fast and effective Tractography Parcellation
White matter fiber clustering (WMFC) is an important strategy for white matter parcellation,
which enables quantitative analysis of white matter connections in health and disease …
which enables quantitative analysis of white matter connections in health and disease …